AI0-001 Implementing AI Solutions Practice Question
A team is implementing a RAG system for a legal document Q&A. They need to chunk documents effectively. Which THREE chunking strategies should they consider to improve retrieval accuracy for legal texts that contain hierarchical sections (clauses, sub-clauses, definitions)?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Hierarchical chunking that indexes chunks at clause and sub-clause levels with parent relationships
Semantic chunking splits at natural boundaries (e.g., paragraphs, sections), preserving meaning. Hierarchical chunking indexes with parent-child relationships for context. Fixed-size chunking is simple but may break sentences or clauses. Overlapping chunks can help but is not a primary strategy for accuracy; sliding window is a specific technique.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Hierarchical chunking that indexes chunks at clause and sub-clause levels with parent relationships
Why this is correct
Allows retrieval of granular chunks while maintaining broader context.
- ✗
Overlapping chunks with a 10% overlap between consecutive chunks
Why it's wrong here
Helps with boundary issues but does not address hierarchical structure; not a primary strategy.
- ✗
Fixed-size chunking with a 512-token window and no overlap
Why it's wrong here
May split clauses mid-sentence, losing context; not ideal for legal structure.
- ✓
Chunking based on the document's table of contents and section hierarchy
Why this is correct
Leverages existing structure; similar to semantic and hierarchical approaches.
- ✓
Semantic chunking that splits at natural boundaries (e.g., section headings, paragraph breaks)
Why this is correct
Preserves logical units of legal text, improving relevance.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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